2_ReportCompositeModellingResults
L Leston
29/04/2020
Model coefficients for the A) AVI-based (AIC= 168.14), B) satellite-based (AIC= 160.34), C) lidar-based (AIC= 145), and D) composite (AIC= 136.11) N-mixture models predicting abundance of Alder Flycatcher Empidonax alnorum, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 284.87), B) satellite-based (AIC= 282.86), C) lidar-based (AIC= 285.99), and D) composite (AIC= 277.73) N-mixture models predicting abundance of American Robin Turdus migratorius, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 126.92), B) satellite-based (AIC= 135.83), C) lidar-based (AIC= 127.93), and D) composite (AIC= 118.64) N-mixture models predicting abundance of Boreal Chickadee Poecile hudsonicus, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 118.63), B) satellite-based (AIC= 126.43), C) lidar-based (AIC= 123.71), and D) composite (AIC= 118.63) N-mixture models predicting abundance of Cedar Waxwing Bombycilla cedrorum, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 566.71), B) satellite-based (AIC= 573), C) lidar-based (AIC= 550.27), and D) composite (AIC= 550.23) N-mixture models predicting abundance of Chipping Sparrow Spizella passerina, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 109.5), B) satellite-based (AIC= 120), C) lidar-based (AIC= 113.58), and D) composite (AIC= 108.68) N-mixture models predicting abundance of Common Yellowthroat Geothlypis trichas, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 422), B) satellite-based (AIC= 436.37), C) lidar-based (AIC= 422.02), and D) composite (AIC= 418.04) N-mixture models predicting abundance of Dark-eyed Junco Junco hyemalis, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 459.33), B) satellite-based (AIC= 460.21), C) lidar-based (AIC= 461.19), and D) composite (AIC= 449.73) N-mixture models predicting abundance of Gray Jay Perisoreus canadensis, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 688.17), B) satellite-based (AIC= 688.84), C) lidar-based (AIC= 676.18), and D) composite (AIC= 673.9) N-mixture models predicting abundance of Hermit Thrush Catharus guttatus, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 243.47), B) satellite-based (AIC= 238.75), C) lidar-based (AIC= 227.99), and D) composite (AIC= 221.14) N-mixture models predicting abundance of Le Conte’s Sparrow Ammodramus lecontei, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 464.25), B) satellite-based (AIC= 465.2), C) lidar-based (AIC= 439.74), and D) composite (AIC= 439.74) N-mixture models predicting abundance of Lincoln’s Sparrow Melospiza lincolnii, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 133.74), B) satellite-based (AIC= 130.55), C) lidar-based (AIC= 126.82), and D) composite (AIC= 126.82) N-mixture models predicting abundance of Olive-sided Flycatcher Contopus cooperi, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 321.36), B) satellite-based (AIC= 334.09), C) lidar-based (AIC= 326.91), and D) composite (AIC= 321.36) N-mixture models predicting abundance of Ovenbird Seiurus aurocapillus, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 153.98), B) satellite-based (AIC= 164.33), C) lidar-based (AIC= 156.91), and D) composite (AIC= 151.97) N-mixture models predicting abundance of Palm Warbler Setophaga palmarum, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 265.41), B) satellite-based (AIC= 280.83), C) lidar-based (AIC= 286.33), and D) composite (AIC= 263.87) N-mixture models predicting abundance of Red-eyed Vireo Vireo olivaceus, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 361.85), B) satellite-based (AIC= 357.62), C) lidar-based (AIC= 355.53), and D) composite (AIC= 353.02) N-mixture models predicting abundance of Ruby-crowned Kinglet Regulus calendula, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 664.61), B) satellite-based (AIC= 657.54), C) lidar-based (AIC= 660.96), and D) composite (AIC= 660.45) N-mixture models predicting abundance of Swainson’s Thrush Catharus ustulatus, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 127.82), B) satellite-based (AIC= 139.33), C) lidar-based (AIC= 138.15), and D) composite (AIC= 127.2) N-mixture models predicting abundance of Swamp Sparrow Melospiza georgiana, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 317.57), B) satellite-based (AIC= 322.11), C) lidar-based (AIC= 322.38), and D) composite (AIC= 317.02) N-mixture models predicting abundance of Tennessee Warbler Leiothlypis peregrina, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 260.39), B) satellite-based (AIC= 269.42), C) lidar-based (AIC= 259.32), and D) composite (AIC= 259.32) N-mixture models predicting abundance of Winter Wren Troglodytes hiemalis, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 318.9), B) satellite-based (AIC= 312.28), C) lidar-based (AIC= 331.48), and D) composite (AIC= 307.17) N-mixture models predicting abundance of White-throated Sparrow Zonotrichia albicollis, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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Model coefficients for the A) AVI-based (AIC= 674.11), B) satellite-based (AIC= 679.02), C) lidar-based (AIC= 678.17), and D) composite (AIC= 671.32) N-mixture models predicting abundance of Yellow-rumped Warbler Setophaga coronata, along with predicted abundances of this species in the Kirby grid from these respective models (E-H).
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